Catalyze open science practices and projects through seminars, workshops, hackathons, contests, proposals, etc.
Join groups within one’s institution to enact changes that promote evaluation/promotion criteria in support of open science practices.
Pursue funding opportunities that require / allow open intellectual property (IP). Leverage research demonstrating the benefits of open IP to negotiate for (more) open IP.
When tasked with an assignment, big or small, opt for open methods where possible (for example, complete a homework assignment using Python, R, or Octave in a shareable Jupyter or R Notebook vs. using a proprietary, licensed product like MATLAB).
Strive toward reproducibility (even for oneself in the future!) by providing self-contained software environments, example input/output data, and clear and updated documentation.
Apply liberal licenses to software (e.g., Apache v2.0) and documentation (e.g., CC0) at the outset of a project.
Forge ties across labs even within an institution to make use of each other’s data/software.
Collaborate with institutions that require open standards.
Use collaborative software (e.g., Google Docs) and where applicable, collaborative software engineering practices with public discussions and issues (e.g., GitHub, GitLab, Bitbucket).
Publish a code of conduct for one’s project to clarify roles and mechanisms for resolving disputes.
Clarify contributor roles at the outset of a publication or project to assign appropriate credit/accountability.
Make it very clear at the outset of a collaboration how open/shared software/data will be acknowledged/rewarded.
Clarify when data/software can be released at the outset of a project.
Avail oneself of experts in alternative/complementary methods to reduce bias, evaluate methods, and corroborate results.
Participate in interdisciplinary, open science and collaboration events (e.g., hackathons, unconferences).
Publications and presentations
Preregister research, and openly publish the preregistration. Publish documents used in preparation for, recruiting for, and execution of the research.
Solicit feedback from scientists and non-scientists alike. Encourage non-scientists to actively participate in publishing and presenting.
Publish and present in venues and in accessible language intended for general audiences. Translate works to other languages. Leverage media other than or in addition to prose and figures (e.g., videos, animations, music).
Publish and present to audiences of relevant disciplines beyond one’s own.
Publish in open access venues and follow FAIR (findable, accessible, interoperable, reusable) principles.
Publish data or software in open data or open methods journals. Follow community-supported data format and reporting guidelines.
Insist on publishing experimental protocols and negative results.
Boycott publishers/publications for review or submission that flout open standards.
When reviewing manuscripts or proposals, acknowledge where attempts are made in support of open science, and point out where greater efforts could be made toward more open science practices. Insist that they follow FAIR principles.
Participate in open peer review, especially for research in languages other than English.
Include an ethics section to articulate ethical considerations and implications.
Study and report the costs and benefits of your own open practices.
Acknowledge, and actively promote, any and all uses of open science in one’s presentations/publications/proposals/lectures and make it clear where people can access these resources. Clearly articulate accessibility of cited resources.
When attending another’s talk or lecture, ask how one can access any software/data/resources that were presented and if there are any usage restrictions.
On one’s webpage & CV, include open resources including data contributions. Complement traditional, citation-based metrics with news and social media coverage.